Overview

Dataset statistics

Number of variables21
Number of observations2624
Missing cells4607
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory430.6 KiB
Average record size in memory168.0 B

Variable types

NUM16
CAT4
BOOL1

Warnings

TempDist has 2351 (89.6%) missing values Missing
SpatDist has 2256 (86.0%) missing values Missing
Duration is highly skewed (γ1 = 29.48313023) Skewed
df_index has unique values Unique
AnzGesperrtFs has 763 (29.1%) zeros Zeros
Length has 756 (28.8%) zeros Zeros
Duration has 421 (16.0%) zeros Zeros

Reproduction

Analysis started2020-11-20 11:05:30.649088
Analysis finished2020-11-20 11:06:53.334306
Duration1 minute and 22.69 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct2624
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1616.889863
Minimum0
Maximum3240
Zeros1
Zeros (%)< 0.1%
Memory size20.5 KiB
2020-11-20T12:06:53.733846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile153.15
Q1774.75
median1622.5
Q32425.25
95-th percentile3084.85
Maximum3240
Range3240
Interquartile range (IQR)1650.5

Descriptive statistics

Standard deviation943.7679253
Coefficient of variation (CV)0.58369339
Kurtosis-1.206850872
Mean1616.889863
Median Absolute Deviation (MAD)825.5
Skewness-0.005704106659
Sum4242719
Variance890697.8967
MonotocityStrictly increasing
2020-11-20T12:06:53.903071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
31351< 0.1%
 
31331< 0.1%
 
10841< 0.1%
 
31311< 0.1%
 
10821< 0.1%
 
31291< 0.1%
 
10801< 0.1%
 
31271< 0.1%
 
10781< 0.1%
 
Other values (2614)261499.6%
 
ValueCountFrequency (%) 
01< 0.1%
 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
ValueCountFrequency (%) 
32401< 0.1%
 
32381< 0.1%
 
32371< 0.1%
 
32361< 0.1%
 
32351< 0.1%
 

TempMax
Real number (ℝ≥0)

Distinct200
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.3365091
Minimum9
Maximum1326
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:54.061587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile15
Q145
median120
Q3228
95-th percentile636
Maximum1326
Range1317
Interquartile range (IQR)183

Descriptive statistics

Standard deviation217.5492178
Coefficient of variation (CV)1.16127507
Kurtosis8.194452249
Mean187.3365091
Median Absolute Deviation (MAD)81
Skewness2.557774526
Sum491571
Variance47327.66217
MonotocityNot monotonic
2020-11-20T12:06:54.216448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
151445.5%
 
361003.8%
 
189672.6%
 
21612.3%
 
24582.2%
 
60481.8%
 
48461.8%
 
18451.7%
 
57411.6%
 
51411.6%
 
Other values (190)197375.2%
 
ValueCountFrequency (%) 
9271.0%
 
12190.7%
 
151445.5%
 
18451.7%
 
21612.3%
 
ValueCountFrequency (%) 
132640.2%
 
1323190.7%
 
13201< 0.1%
 
11941< 0.1%
 
1116120.5%
 

TempAvg
Real number (ℝ≥0)

Distinct244
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.71989329
Minimum5
Maximum1326
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:54.370718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9
Q122
median53
Q3109
95-th percentile267.8
Maximum1326
Range1321
Interquartile range (IQR)87

Descriptive statistics

Standard deviation102.3310154
Coefficient of variation (CV)1.193783747
Kurtosis24.97426707
Mean85.71989329
Median Absolute Deviation (MAD)37
Skewness3.676119237
Sum224929
Variance10471.63672
MonotocityNot monotonic
2020-11-20T12:06:54.516002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
151415.4%
 
162582.2%
 
31582.2%
 
30481.8%
 
12451.7%
 
17421.6%
 
18421.6%
 
21401.5%
 
9381.4%
 
70381.4%
 
Other values (234)207479.0%
 
ValueCountFrequency (%) 
560.2%
 
6311.2%
 
7321.2%
 
8271.0%
 
9381.4%
 
ValueCountFrequency (%) 
132620.1%
 
96620.1%
 
67330.1%
 
58140.2%
 
5751< 0.1%
 

SpatMax
Real number (ℝ≥0)

Distinct1085
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9241.61471
Minimum699
Maximum49765
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:54.655449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum699
5-th percentile1641
Q12831
median5688
Q312370.25
95-th percentile29357.1
Maximum49765
Range49066
Interquartile range (IQR)9539.25

Descriptive statistics

Standard deviation9219.142637
Coefficient of variation (CV)0.9975683823
Kurtosis3.404716733
Mean9241.61471
Median Absolute Deviation (MAD)3240
Skewness1.843409412
Sum24249997
Variance84992590.96
MonotocityNot monotonic
2020-11-20T12:06:54.806366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
28311104.2%
 
1926532.0%
 
1014391.5%
 
2908240.9%
 
8459220.8%
 
3306200.8%
 
2226190.7%
 
2475190.7%
 
1903140.5%
 
11282140.5%
 
Other values (1075)229087.3%
 
ValueCountFrequency (%) 
6991< 0.1%
 
9021< 0.1%
 
9651< 0.1%
 
99120.1%
 
1014391.5%
 
ValueCountFrequency (%) 
4976530.1%
 
489871< 0.1%
 
4760760.2%
 
4719630.1%
 
447511< 0.1%
 

SpatAvg
Real number (ℝ≥0)

Distinct1156
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3356.083841
Minimum284
Maximum15602
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:54.958794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum284
5-th percentile889
Q11536
median2378
Q34210.25
95-th percentile9616
Maximum15602
Range15318
Interquartile range (IQR)2674.25

Descriptive statistics

Standard deviation2737.973423
Coefficient of variation (CV)0.8158239043
Kurtosis3.684917889
Mean3356.083841
Median Absolute Deviation (MAD)1011
Skewness1.905024754
Sum8806364
Variance7496498.464
MonotocityNot monotonic
2020-11-20T12:06:55.110056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
15361104.2%
 
1575532.0%
 
809391.5%
 
2691210.8%
 
1683200.8%
 
1276170.6%
 
2469150.6%
 
1272150.6%
 
4430140.5%
 
12363130.5%
 
Other values (1146)230787.9%
 
ValueCountFrequency (%) 
2841< 0.1%
 
30530.1%
 
3551< 0.1%
 
4041< 0.1%
 
4571< 0.1%
 
ValueCountFrequency (%) 
1560220.1%
 
1559020.1%
 
1505440.2%
 
1478530.1%
 
147761< 0.1%
 

TempDist
Real number (ℝ≥0)

MISSING

Distinct24
Distinct (%)8.8%
Missing2351
Missing (%)89.6%
Infinite0
Infinite (%)0.0%
Mean11.13186813
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:55.263665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median10
Q315
95-th percentile22
Maximum24
Range23
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.039469672
Coefficient of variation (CV)0.5425387366
Kurtosis-0.8019439214
Mean11.13186813
Median Absolute Deviation (MAD)4
Skewness0.3226704522
Sum3039
Variance36.47519392
MonotocityNot monotonic
2020-11-20T12:06:55.404647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
6210.8%
 
9200.8%
 
10180.7%
 
7160.6%
 
14150.6%
 
11140.5%
 
15140.5%
 
3130.5%
 
12130.5%
 
8120.5%
 
Other values (14)1174.5%
 
(Missing)235189.6%
 
ValueCountFrequency (%) 
170.3%
 
290.3%
 
3130.5%
 
4120.5%
 
5110.4%
 
ValueCountFrequency (%) 
2460.2%
 
2340.2%
 
2250.2%
 
21100.4%
 
20100.4%
 

SpatDist
Real number (ℝ≥0)

MISSING

Distinct228
Distinct (%)62.0%
Missing2256
Missing (%)86.0%
Infinite0
Infinite (%)0.0%
Mean696.1902174
Minimum1
Maximum1988
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:55.553643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile34.05
Q1152
median576
Q31073.5
95-th percentile1843.15
Maximum1988
Range1987
Interquartile range (IQR)921.5

Descriptive statistics

Standard deviation583.0091878
Coefficient of variation (CV)0.8374280092
Kurtosis-0.7157057295
Mean696.1902174
Median Absolute Deviation (MAD)454
Skewness0.668566729
Sum256198
Variance339899.713
MonotocityNot monotonic
2020-11-20T12:06:55.696835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
576391.5%
 
92381.4%
 
1025170.6%
 
198570.3%
 
43160.2%
 
198640.2%
 
140.2%
 
58830.1%
 
18230.1%
 
9730.1%
 
Other values (218)2449.3%
 
(Missing)225686.0%
 
ValueCountFrequency (%) 
140.2%
 
220.1%
 
520.1%
 
81< 0.1%
 
920.1%
 
ValueCountFrequency (%) 
19881< 0.1%
 
198640.2%
 
198570.3%
 
19821< 0.1%
 
19561< 0.1%
 

Coverage
Real number (ℝ≥0)

Distinct94
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.13033537
Minimum4
Maximum100
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:55.865277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile14
Q129
median45
Q362
95-th percentile85
Maximum100
Range96
Interquartile range (IQR)33

Descriptive statistics

Standard deviation21.97233752
Coefficient of variation (CV)0.4763099455
Kurtosis-0.6621426759
Mean46.13033537
Median Absolute Deviation (MAD)16
Skewness0.341124255
Sum121046
Variance482.7836162
MonotocityNot monotonic
2020-11-20T12:06:56.173671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
481485.6%
 
35783.0%
 
27682.6%
 
85652.5%
 
64602.3%
 
79582.2%
 
32532.0%
 
34522.0%
 
47511.9%
 
38481.8%
 
Other values (84)194374.0%
 
ValueCountFrequency (%) 
430.1%
 
690.3%
 
790.3%
 
8100.4%
 
9130.5%
 
ValueCountFrequency (%) 
100311.2%
 
991< 0.1%
 
9730.1%
 
9570.3%
 
9460.2%
 

TempGL
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
3
1695 
2
643 
1
282 
4
 
4
ValueCountFrequency (%) 
3169564.6%
 
264324.5%
 
128210.7%
 
440.2%
 
2020-11-20T12:06:56.324590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T12:06:56.424664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:56.531886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

SpatGL
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2
2256 
3
368 
ValueCountFrequency (%) 
2225686.0%
 
336814.0%
 
2020-11-20T12:06:56.646244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T12:06:56.725445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:56.802997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

TempIL
Real number (ℝ)

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.068597561
Minimum-1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:56.896075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median3
Q34
95-th percentile5
Maximum5
Range6
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.369076773
Coefficient of variation (CV)1.145257453
Kurtosis-1.552752615
Mean2.068597561
Median Absolute Deviation (MAD)2
Skewness-0.3596672682
Sum5428
Variance5.612524758
MonotocityNot monotonic
2020-11-20T12:06:56.976488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
-192935.4%
 
379430.3%
 
448218.4%
 
540515.4%
 
280.3%
 
160.2%
 
ValueCountFrequency (%) 
-192935.4%
 
160.2%
 
280.3%
 
379430.3%
 
448218.4%
 
ValueCountFrequency (%) 
540515.4%
 
448218.4%
 
379430.3%
 
280.3%
 
160.2%
 

SpatIL
Real number (ℝ)

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.730182927
Minimum-1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:57.077819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q12
median3
Q34
95-th percentile5
Maximum5
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.911397035
Coefficient of variation (CV)0.7000985231
Kurtosis-0.4791336765
Mean2.730182927
Median Absolute Deviation (MAD)1
Skewness-0.7049981926
Sum7164
Variance3.653438625
MonotocityNot monotonic
2020-11-20T12:06:57.163861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
461123.3%
 
253920.5%
 
551519.6%
 
342216.1%
 
-136814.0%
 
11696.4%
 
ValueCountFrequency (%) 
-136814.0%
 
11696.4%
 
253920.5%
 
342216.1%
 
461123.3%
 
ValueCountFrequency (%) 
551519.6%
 
461123.3%
 
342216.1%
 
253920.5%
 
11696.4%
 

TLCar
Real number (ℝ≥0)

Distinct714
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1503.476372
Minimum1000
Maximum1999
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:57.284793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1051
Q11277
median1523
Q31750
95-th percentile1938
Maximum1999
Range999
Interquartile range (IQR)473

Descriptive statistics

Standard deviation282.307127
Coefficient of variation (CV)0.1877695801
Kurtosis-1.151516292
Mean1503.476372
Median Absolute Deviation (MAD)237
Skewness-0.06950558419
Sum3945122
Variance79697.31397
MonotocityNot monotonic
2020-11-20T12:06:57.433104image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
15551094.2%
 
1297532.0%
 
1286391.5%
 
1152220.8%
 
1518220.8%
 
1667200.8%
 
1659170.6%
 
1015170.6%
 
1323160.6%
 
1403150.6%
 
Other values (704)229487.4%
 
ValueCountFrequency (%) 
100030.1%
 
1001100.4%
 
100350.2%
 
100430.1%
 
100540.2%
 
ValueCountFrequency (%) 
19991< 0.1%
 
199720.1%
 
199660.2%
 
199540.2%
 
199120.1%
 

TLHGV
Real number (ℝ≥0)

Distinct465
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean732.5560213
Minimum500
Maximum999
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:57.567888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile513
Q1612
median734.5
Q3849
95-th percentile971
Maximum999
Range499
Interquartile range (IQR)237

Descriptive statistics

Standard deviation143.8753826
Coefficient of variation (CV)0.1964018838
Kurtosis-1.110121605
Mean732.5560213
Median Absolute Deviation (MAD)120.5
Skewness0.1351401133
Sum1922227
Variance20700.12572
MonotocityNot monotonic
2020-11-20T12:06:57.717874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7871174.5%
 
505552.1%
 
612451.7%
 
738321.2%
 
513230.9%
 
987220.8%
 
737220.8%
 
671190.7%
 
846190.7%
 
571190.7%
 
Other values (455)225185.8%
 
ValueCountFrequency (%) 
50050.2%
 
50150.2%
 
50290.3%
 
50320.1%
 
50440.2%
 
ValueCountFrequency (%) 
99950.2%
 
99820.1%
 
997170.6%
 
99670.3%
 
99550.2%
 

Strasse
Categorical

Distinct17
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
A 3
884 
A 9
562 
A 7
239 
A 99
225 
A 96
177 
Other values (12)
537 
ValueCountFrequency (%) 
A 388433.7%
 
A 956221.4%
 
A 72399.1%
 
A 992258.6%
 
A 961776.7%
 
A 61616.1%
 
A 931284.9%
 
A 92682.6%
 
A 73672.6%
 
A 94431.6%
 
Other values (7)702.7%
 
2020-11-20T12:06:57.854902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T12:06:57.978646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length3
Mean length3.302591463
Min length3

AnzGesperrtFs
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7016006098
Minimum-1
Maximum3
Zeros763
Zeros (%)29.1%
Memory size20.5 KiB
2020-11-20T12:06:58.328272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum3
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4843542488
Coefficient of variation (CV)0.690356083
Kurtosis-0.04465654628
Mean0.7016006098
Median Absolute Deviation (MAD)0
Skewness-0.8475431605
Sum1841
Variance0.2345990383
MonotocityNot monotonic
2020-11-20T12:06:58.441819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
1183269.8%
 
076329.1%
 
-1170.6%
 
2100.4%
 
320.1%
 
ValueCountFrequency (%) 
-1170.6%
 
076329.1%
 
1183269.8%
 
2100.4%
 
320.1%
 
ValueCountFrequency (%) 
320.1%
 
2100.4%
 
1183269.8%
 
076329.1%
 
-1170.6%
 

Einzug
Real number (ℝ≥0)

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.483231707
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size20.5 KiB
2020-11-20T12:06:58.561597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.61049529
Coefficient of variation (CV)0.6485481341
Kurtosis-1.106773323
Mean2.483231707
Median Absolute Deviation (MAD)1
Skewness0.7690026967
Sum6516
Variance2.59369508
MonotocityNot monotonic
2020-11-20T12:06:58.651823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
297937.3%
 
191034.7%
 
572127.5%
 
3130.5%
 
41< 0.1%
 
ValueCountFrequency (%) 
191034.7%
 
297937.3%
 
3130.5%
 
41< 0.1%
 
572127.5%
 
ValueCountFrequency (%) 
572127.5%
 
41< 0.1%
 
3130.5%
 
297937.3%
 
191034.7%
 

Richtung
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
1
2567 
0
 
57
ValueCountFrequency (%) 
1256797.8%
 
0572.2%
 
2020-11-20T12:06:58.730495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Length
Real number (ℝ≥0)

ZEROS

Distinct1237
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean947.3410823
Minimum0
Maximum24500
Zeros756
Zeros (%)28.8%
Memory size20.5 KiB
2020-11-20T12:06:58.813920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median292
Q31228.25
95-th percentile3988.35
Maximum24500
Range24500
Interquartile range (IQR)1228.25

Descriptive statistics

Standard deviation1695.512711
Coefficient of variation (CV)1.78975951
Kurtosis35.62129468
Mean947.3410823
Median Absolute Deviation (MAD)292
Skewness4.552555278
Sum2485823
Variance2874763.354
MonotocityNot monotonic
2020-11-20T12:06:58.960958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
075628.8%
 
100180.7%
 
200100.4%
 
150100.4%
 
300100.4%
 
6590.3%
 
50080.3%
 
5270.3%
 
40070.3%
 
9760.2%
 
Other values (1227)178367.9%
 
ValueCountFrequency (%) 
075628.8%
 
81< 0.1%
 
101< 0.1%
 
261< 0.1%
 
271< 0.1%
 
ValueCountFrequency (%) 
245001< 0.1%
 
210321< 0.1%
 
174301< 0.1%
 
141851< 0.1%
 
1380020.1%
 

Duration
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct482
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean360.5826982
Minimum0
Maximum187650
Zeros421
Zeros (%)16.0%
Memory size20.5 KiB
2020-11-20T12:06:59.251641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median30
Q398
95-th percentile553.85
Maximum187650
Range187650
Interquartile range (IQR)94

Descriptive statistics

Standard deviation4964.152373
Coefficient of variation (CV)13.76702875
Kurtosis983.8578272
Mean360.5826982
Median Absolute Deviation (MAD)30
Skewness29.48313023
Sum946169
Variance24642808.78
MonotocityNot monotonic
2020-11-20T12:06:59.391155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
042116.0%
 
1913.5%
 
4732.8%
 
2642.4%
 
3622.4%
 
7411.6%
 
5411.6%
 
9361.4%
 
6321.2%
 
15301.1%
 
Other values (472)173366.0%
 
ValueCountFrequency (%) 
042116.0%
 
1913.5%
 
2642.4%
 
3622.4%
 
4732.8%
 
ValueCountFrequency (%) 
1876501< 0.1%
 
1320601< 0.1%
 
753301< 0.1%
 
391801< 0.1%
 
321301< 0.1%
 

Month
Categorical

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
Jul
455 
Sep
303 
Oct
237 
Dec
232 
Aug
228 
Other values (7)
1169 
ValueCountFrequency (%) 
Jul45517.3%
 
Sep30311.5%
 
Oct2379.0%
 
Dec2328.8%
 
Aug2288.7%
 
Apr2268.6%
 
May2017.7%
 
Mar1806.9%
 
Nov1736.6%
 
Jun1495.7%
 
Other values (2)2409.1%
 
2020-11-20T12:06:59.543725image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T12:06:59.664904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Interactions

2020-11-20T12:05:36.347746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:37.849217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:39.278719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:40.601777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:41.978684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:43.422724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:44.916208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:46.359108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:47.672975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:49.023040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:50.343526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:51.696917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:53.091105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:54.425490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:55.935829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:57.459119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:59.810706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:59.829240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:05:59.949569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:00.076887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:00.202649image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:00.321313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:01.250519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:01.401312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:01.530445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.123047image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.238433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.383397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.509283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.623673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.754354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:02.876380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:04.558760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:04.576906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:04.688596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:04.801383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:04.906664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.011813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.144868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.265374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.391651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.502492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.604941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.741203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.868924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:05.977265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:06.098350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:06.224163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:07.902767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:07.923297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.039447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.140996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.238150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.344916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.475531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.583565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.697394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.806902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:08.910204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:09.030250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:09.135604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:09.231617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:09.350339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:09.477763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.173203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.194213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.293544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.400324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.499704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.587241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.687340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.785541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.890318image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:11.981391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.072883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.177617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.269419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.371584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.477306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:12.574073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.189081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.207906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.341128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.471516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.590356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.695709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.811548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:14.940734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.062310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.185209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.314176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.455037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.572568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.699755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.845494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:15.981706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.477520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.498435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.609119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.727534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.840344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:17.943945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:18.057280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:18.159641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:19.427105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:19.534829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:19.649112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:19.776768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:19.895616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:20.001898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:20.164057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:20.294000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:21.963826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:21.984397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.102940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.225141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.344650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.466123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.593986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.699692image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.807053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:22.914715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.034578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.158717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.269035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.365708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.489225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:23.648141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.309976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.331376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.452573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.552114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.653221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.744681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.867030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:25.971529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.235317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.343535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.451611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.567555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.662026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.763075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.868277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:26.972147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.541045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.560135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.662244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.763356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.860106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:28.944001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.053436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.167959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.276738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.390852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.500506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.615574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.723656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.827879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:29.937616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:30.035500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:31.637413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:31.655162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:31.774946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:31.890125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:31.999087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.100084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.212168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.319320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.598841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.719426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.839259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:32.964819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:33.084404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:33.200986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:33.327264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:33.441666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:34.913127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:34.934806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.041201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.139035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.240927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.330880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.445269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.550681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.645220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.737503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.826602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:35.924387image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:36.024889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:36.117850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:36.220742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:36.316887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:37.699815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:37.717759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:37.817054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:37.919697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.014414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.103627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.203766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.304672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.564747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.665970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.756743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.856732image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:38.948453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:39.040212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:39.147585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:39.244270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:40.674502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:40.694700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:40.808346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:40.921164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.026078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.127681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.245963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.356743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.472253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.575166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.678329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.794735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:41.901080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:42.004057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:42.120089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:42.230894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:43.614013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:43.634721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:43.742930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:43.846692image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:43.946744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.041320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.148821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.419815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.526864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.622794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.719850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.831320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:44.926450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:45.027795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:45.137275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:45.240813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:46.611811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:46.629579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:46.737189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:46.834037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:46.934539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.026967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.128558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.231899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.330828image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.427902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.521707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.626677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.723567image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.816878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:47.924872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:48.026851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-20T12:07:01.039961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-20T12:07:02.467302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-20T12:07:03.872128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-20T12:07:05.194228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-20T12:07:05.235955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-20T12:06:49.861622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:51.517122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:51.616583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T12:06:53.298112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTempGLSpatGLTempILSpatILTLCarTLHGVStrasseAnzGesperrtFsEinzugRichtungLengthDurationMonth
006930151833134NaNNaN1832321966954A 9121018Jan
116930151833134NaNNaN1822-141966954A 91111377247Jan
226930151833134NaNNaN1832321966954A 90516361Jan
3333653011317NaNNaN1732331131856A 9121410Jan
4433653011317NaNNaN1722-121131856A 9051260345Jan
5533653011317NaNNaN1732441131856A 90512588Jan
661741561543213788NaNNaN8832211388591A 71111322143Jan
77572322101205NaNNaN5122-151143580A 701213246407Jan
810604320561310NaNNaN7322-131450543A 70120062Jan
911601761581409NaNNaN2132321742834A 6121391237Jan

Last rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTempGLSpatGLTempILSpatILTLCarTLHGVStrasseAnzGesperrtFsEinzugRichtungLengthDurationMonth
261432293603061406312907NaNNaN9132331884934A 312103Dec
26153230753565542934NaNNaN4322-151853799A 3111122881Dec
26163232753565542934NaN702.043334-11853799A 305163920Dec
26173233816126982360NaNNaN8632441305511A 711158560Dec
26183234816126982360NaNNaN8632321305511A 70518511Dec
26193235816126982360NaNNaN8632441305511A 7-11130075Dec
262032366017122194654NaNNaN3732321671871A 905111611Dec
262132376017122194654NaNNaN3732311671871A 91213054Dec
262232386017122194654NaNNaN3732311671871A 90511291Dec
2623324039212218967NaNNaN4222-121003565A 73121151839Dec